OFDM系统中基于EM迭代的时变信道估计与数据检测

针对OFDM系统中难以实时获取时变信道统计信息的问题，提出了一种基于期望最大化(EM, expectation maximization)迭代的多符号联合信道估计和数据检测算法。为了获取合适的迭代初始值，利用梳状导频的信息，设计了基于最小二乘算法的低复杂度的初始化方案。通过分析算法中的信道统计量与信噪比的关系，提出了忽略信道自相关矩阵的简化算法，避免了获取信道统计信息的操作。仿真结果表明，提出的算法对信道的功率延迟分布和多普勒功率谱等统计信息不敏感，在未知信道多普勒功率谱的条件下，仍然具有较低的估计误差和误码率。 

Time-varying channel estimation and data detection for OFDM systems via the EM iteration

Due to the difficulty in obtaining real-time statistics of time-varying channels, a multi-symbol channel estimation and data detection algorithm based on the expectation-maximization (EM) iteration was proposed for OFDM systems. In order to obtain a proper initial estimate for the iteration, a LS-based low-complexity scheme was implemented by making use of comb-type pilots. With the relationship between the channel statistics and signal to noise ratio in the proposed algorithm, a simplified algorithm with the channel autocorrelation matrix ignored was also introduced, and hence the operation of estimating channel statistics was avoided. Simulation results validate its robust properties to the absence of exact channel statistics such as power delay profile and Doppler power spectrum, and show that the normalized mean squared error and the bit error rate can be significantly reduced by this algorithm without exact Doppler power spectrum.